{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# DFN model for sodium-ion batteries\n",
    "\n",
    "In this notebook we use the DFN model to simulate sodium-ion batteries. The parameters are based on the article\n",
    "> K. Chayambuka, G. Mulder, D.L. Danilov, P.H.L. Notten, Physics-based modeling of sodium-ion batteries part II. Model and validation, Electrochimica Acta 404 (2022) 139764. https://doi.org/10.1016/j.electacta.2021.139764.\n",
    "\n",
    "However, the specific values (including the data for the interpolants) are taken from the COMSOL implementation presented in [this example](https://www.comsol.com/model/1d-isothermal-sodium-ion-battery-117341). As usual, we start by importing PyBaMM."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "An NVIDIA GPU may be present on this machine, but a CUDA-enabled jaxlib is not installed. Falling back to cpu.\n"
     ]
    }
   ],
   "source": [
    "import pybamm"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We now need to define the model. In this case we take the `BasicDFN` model for sodium-ion batteries (note how it is called from the `pybamm.sodium_ion` submodule). Note that, at the moment, the model is identical to the one for lithium-ion batteries, but uses different parameter values."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "model = pybamm.sodium_ion.BasicDFN()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "In order to replicate the results in the COMSOL example, we discharge at different C-rates and compare the solutions. We loop over the C-rate dictionary and solve the model for each C-rate. We append the solutions into a list so we can later plots the results."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "8ca3353c637e48d28c3b02f42d25fa03",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(FloatSlider(value=0.0, description='t', max=10.80914150213347, step=0.1080914150213347),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<pybamm.plotting.quick_plot.QuickPlot at 0x7f9763ff3e90>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "C_rates = [1 / 12, 5 / 12, 10 / 12, 1]\n",
    "solutions = []\n",
    "\n",
    "for C_rate in C_rates:\n",
    "    sim = pybamm.Simulation(model, C_rate=C_rate)\n",
    "    sol = sim.solve([0, 4000 / C_rate])\n",
    "    solutions.append(sol)\n",
    "\n",
    "pybamm.dynamic_plot(solutions)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We can now perform a manual plot of voltage versus capacity, to compare the results with the COMSOL example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "\n",
    "for solution, C_rate in zip(solutions, C_rates, strict=False):\n",
    "    capacity = [i * 1000 for i in solution[\"Discharge capacity [A.h]\"].entries]\n",
    "    voltage = solution[\"Voltage [V]\"].entries\n",
    "    plt.plot(capacity, voltage, label=f\"{(12 * C_rate)} A.m-2\")\n",
    "\n",
    "plt.xlabel(\"Discharge Capacity [mA.h]\")\n",
    "plt.ylabel(\"Voltage [V]\");"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[1] Joel A. E. Andersson, Joris Gillis, Greg Horn, James B. Rawlings, and Moritz Diehl. CasADi – A software framework for nonlinear optimization and optimal control. Mathematical Programming Computation, 11(1):1–36, 2019. doi:10.1007/s12532-018-0139-4.\n",
      "[2] Kudakwashe Chayambuka, Grietus Mulder, Dmitri L Danilov, and Peter HL Notten. Physics-based modeling of sodium-ion batteries part ii. model and validation. Electrochimica Acta, 404:139764, 2022.\n",
      "[3] Charles R. Harris, K. Jarrod Millman, Stéfan J. van der Walt, Ralf Gommers, Pauli Virtanen, David Cournapeau, Eric Wieser, Julian Taylor, Sebastian Berg, Nathaniel J. Smith, and others. Array programming with NumPy. Nature, 585(7825):357–362, 2020. doi:10.1038/s41586-020-2649-2.\n",
      "[4] Alan C. Hindmarsh. The PVODE and IDA algorithms. Technical Report, Lawrence Livermore National Lab., CA (US), 2000. doi:10.2172/802599.\n",
      "[5] Alan C. Hindmarsh, Peter N. Brown, Keith E. Grant, Steven L. Lee, Radu Serban, Dan E. Shumaker, and Carol S. Woodward. SUNDIALS: Suite of nonlinear and differential/algebraic equation solvers. ACM Transactions on Mathematical Software (TOMS), 31(3):363–396, 2005. doi:10.1145/1089014.1089020.\n",
      "[6] Scott G. Marquis, Valentin Sulzer, Robert Timms, Colin P. Please, and S. Jon Chapman. An asymptotic derivation of a single particle model with electrolyte. Journal of The Electrochemical Society, 166(15):A3693–A3706, 2019. doi:10.1149/2.0341915jes.\n",
      "[7] Valentin Sulzer, Scott G. Marquis, Robert Timms, Martin Robinson, and S. Jon Chapman. Python Battery Mathematical Modelling (PyBaMM). Journal of Open Research Software, 9(1):14, 2021. doi:10.5334/jors.309.\n",
      "\n"
     ]
    }
   ],
   "source": [
    "pybamm.print_citations()"
   ]
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